Humanities in the Data Classroom

John R. Ladd

DH 2024, jrladd.com/slides/humanities-ds

The Future of Code and Data Work

Some Definitions

On the one hand, it’s bringing the tools and techniques of digital media to bear on traditional humanistic questions. But it’s also bringing humanistic modes of inquiry to bear on digital media.

Kathleen Fitzpatrick, 2015

[T]he computational study of culture. … [S]cholarship that applies computational and quantitative methods to the study of cultural objects (sound, image, text), cultural processes (reading, listening, searching, sorting, hierarchizing) and cultural agents (artists, editors, producers, composers).

Journal of Cultural Analytics

The Data Science Curriculum

Pedagogical approaches

  • DH in the Humanities classroom
  • DH in the DH classroom
  • DH in the Data Science classroom?

Intro to Data Science

At the end of this course, you should be able to:

  • Understand and implement the data analysis process, from data collection to communicating results.
  • Use exploratory data analysis to quickly understand a complex dataset.
  • Apply modeling techniques to make predictions.
  • Evaluate the effectiveness of different modeling techniques.
  • Think and act ethically at all steps of the data analysis process.

Network Analysis Course

At the end of this course, you should be able to:

  • Identify the basic types of networks and understand the techniques used to determine their structure.
  • Outline the history of network analysis and its relationship to global economic, political, and social trends.
  • Enhance the analysis and comprehension of networks with visualization.
  • Develop network models appropriate to specific knowledge domains.
  • Analyze complex problems in a number of disciplines with network models.

Ways Humanities Data Can Intervene

Foundational approaches

[D]ata science is often framed as an abstract and technical pursuit. Steps like cleaning and wrangling data are presented as solely technical conundrums; there is less discussion of the social context, ethics, values, or politics of data. This perpetuates the myth that data science about astrophysics is the same as data science about criminal justice is the same as data science about carbon emissions. This limits the transformative work that can be done.

D’Ignazio and Klein, Data Feminism Ch. 2, 2020

Data science educators around the world have begun to recognize the importance of human-centered approaches to the field to help students understand the risks and benefits of data science analysis (Anderson & Parker, 2019; Aragon et al., 2016;Wu et al., 2020). Integrating the humanities into the data science curriculum could also provide a road to a “science identity” for students who lack one, by spotlighting the type of creative and big-picture thinking that such students fear the discipline is missing (Sjøberg, 2002; Steele et al., 1974; Tobias, 1993; Valenti et al., 2016).

Eric A. Vance, et al., “Integrating the Humanities into Data Science Education: Reimagining the Introductory Data Science Course”

Ethics and Data in Context

Familiarity

Unstructured Data

Problem Formulation

DS as a discipline

Humanities data isn’t an “extra”

It’s an essential part of data literacy education and introducing undergraduates to code and data work.